docstr: Parameters
  ----------
  fields : list of str
     'open', 'high', 'low', 'close', or 'volume'
  start_dt: Timestamp
     Beginning of the window range.
  end_dt: Timestamp
     End of the window range.
  sids : list of int
     The asset identifiers in the window.
  
  Returns
  -------
  list of np.ndarray
      A list with an entry per field of ndarrays with shape
      (minutes in range, sids) with a dtype of float64, containing the
      values for the respective field over start and end dt range.
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code: def load_raw_arrays(self, fields, start_dt, end_dt, sids):
      """
      Parameters
      ----------
      fields : list of str
         'open', 'high', 'low', 'close', or 'volume'
      start_dt: Timestamp
         Beginning of the window range.
      end_dt: Timestamp
         End of the window range.
      sids : list of int
         The asset identifiers in the window.
  
      Returns
      -------
      list of np.ndarray
          A list with an entry per field of ndarrays with shape
          (minutes in range, sids) with a dtype of float64, containing the
          values for the respective field over start and end dt range.
      """
      start_idx = self._find_position_of_minute(start_dt)
      end_idx = self._find_position_of_minute(end_dt)
  
      periods = (
          self.calendar.minutes_in_range(start_dt, end_dt)
          if self.data_frequency == "minute"
          else self.calendar.sessions_in_range(start_dt, end_dt)
      )
  
      num_days = len(periods)
      shape = num_days, len(sids)
  
      all_fields = fields[:]
      if len(all_fields) == 1 and all_fields[0] == "volume":
          all_fields.insert(0, "close")
  
      mask = None
      data = []
      for field in all_fields:
          if field != "volume":
              out = np.full(shape, np.nan)
          else:
              out = np.zeros(shape, dtype=np.float64)
  
          for i, sid in enumerate(sids):
              carray = self._open_minute_file(field, sid)
              a = carray[start_idx : end_idx + 1]
  
              if mask is None:
                  mask = a != 0
  
              inverse_ratio = self._ohlc_ratio_inverse_for_sid(sid)
              out[: len(mask), i][mask] = a[mask] * inverse_ratio
  
          if field in fields:
              data.append(out)
  
      return data
  
file_path: catalyst/catalyst/exchange/exchange_bcolz.py
imports: import numpy
  from catalyst import get_calendar
  from catalyst.data.minute_bars import BcolzMinuteBarReader, BcolzMinuteBarWriter
label_desc: Use image node_id 3 for calling the BcolzExchangeBarReader obj's underlying member method code with example usage: obj.load_raw_arrays(fields, start_dt, end_dt, sids) and returns: data